I am using Stata 15.1 with zinb. My dependent variable is number of times a respondent used a tanning bed in the past year (tanning). I zinb tanning on my variable of interest, log income, to obtain an income elasticity estimate. Other regressors include age, educational attainment, race, ethnicity, health status, employment status marital status, family size, time dummies, and region dummies. Specifically, my estimation commands are:

local xlist1 "log_income age doctoral professional masters bachelors associates somecollege highschool black white hispanic employed unemployed hourswrk married livingwpartner widowed divorcedseparated health famsize"

zinb tanning `xlist1' i.region i.year [pw=sampweight], vce(robust) inflate(`xlist1' i.region i.year)

Gender is another variable of interest. I am specifically wanting to know if there is a statistically significant difference between the income elasticity for men and the income elasticity for women. When I attempt to interact a gender dummy, female, with log_income and run zinb again, zinb will not converge. Specifically, I run the following:

gen log_income_female=log_income*female;

local xlist2 "log_income log_income_female age doctoral professional masters bachelors associates somecollege highschool black white hispanic employed unemployed hourswrk married livingwpartner widowed divorcedseparated health famsize"

zinb tanning`xlist2' i.region i.year [pw=sampweight], vce(robust) inflate(`xlist2' i.region i.year)

I suspect that non-convergence is due to perfect prediction of the logit estimation run in the inflate portion of zinb. My question is is there anything I do to get around the non-convergence and test whether log_income_female is statistically significant?

Please note I that have evaluated zinb vs. nbreg in an earlier part of my analysis and comparison of AIC and BIC indicates that zinb is what I should use.